Here is a research paper that discusses using adiabatic quantum computation using liquid state nuclear magnetic resonance quantum computers for pattern recognition.
Pattern recognition is a critical aspect of artificial intelligence. I have a new article “Artificial Intelligence: You are soaking in it”, which discusses mostly ignored penetration of artificial intellience and its future with a lot of links to my articles on near terms pathways to computers millions of times more powerful than todays.
A novel quantum pattern recognition scheme is presented, which combines the idea of a
classic Hopfield neural network [shown to the left] with quantum adiabatic computation. Both the input and the memorized patterns are represented by means of the problem Hamiltonian. In contrast to classic neural networks, the algorithm can simultaneously return multiple recognized patterns. The approach also promises extension of classic memory capacity. A proof of principle for the algorithm for two qubits is provided using a liquid state NMR quantum computer.
In contrast to classic neural networks, a quantum neural register can represent a superposition of recognized patterns. Quantum superposition allows each of these patterns to be identified which is not the case for linearly combined mixture states in classic neural networks.
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